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155 results for “small river”
Small mammal captures per 100 trap nights at the 2007 Anaktuvuk River fire scar and nearby unburned site, sampled in 2014, 2017-2019.
Small mammals (rodents and shrews) were sampled 7-12 years following the Anaktuvuk River Fire to examine how post-fire ecological changes influence small mammal abundance. Small mammals were snap-trapped in August 2014, 2017-2019 at the site of the 2007 Anaktuvuk River Fire, and a nearby unburned control site. At each site, 120 traps were set in 3 parallel lines spaced 40m apart. Each trap was spaced 10m apart, baited, and set to rodent sign within one meter of the trap station. Traps were checked the following two mornings with all captures collected and sprung traps reset. Abundance estimates (captures per 100 trap nights) are presented for tundra voles (Microtus oeconomus), red-backed voles (Myodes rutilus) and shrews (Sorex spp.) The goals of the project were to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
Small reservoir grab sample data, Parker, Ipswich, Lamprey, and Oyster River Watersheds, 2015 - 2020
This dataset contains water quality data from the inputs and outputs of eight reservoirs located in southeastern New Hampshire and northeastern Massachusetts. Samples were filtered in the field using Whatman GF/F filters with a nominal pore size of 0.7 µm and stored on ice until returned to the lab where they were frozen until analysis. Samples were analyzed for anions (NO3-, Cl-, SO4-, Br-) via ion chromatography on a Dionex Ion Chromatograph; NH4+ using a colorimetric method on a SmartChem Chemistry Analyzer; and total dissolved nitrogen (TDN) and dissolved organic carbon (DOC) via high-temperature oxidation on a Shimadzu TOC-V. DON was calculated as the difference between TDN and DIN (NO3- + NH4+). Samples correspond with individual sample names. Site (n = 8) indicate which reservoir each sample belongs to. Location indicates whether a sample was collected at the outflow or inflow ("UP", for reservoirs with one inflow) or "UP_1", "UP_2", or "UP_3" for sites with up to three inflows. CArea.km2 is the upstream drainage area estimated from the reservoir outflow while SArea.km2 is the surface area of each reservoir calculated via NHD+ polygons in GIS software. Temp.C is water temperature at the reservoir outflow on the day of sample collection while Discharge.m3s is the daily discharge scaled to the reservoir outflow from the nearest USGS gaging station. DIN.mgL, DON.mgL, and TDN.mgL are concentrations of dissolved inorganic nitrogen, dissolved organic nitrogen, and total dissolved nitrogen, respectively, in mg/L.
Fig. 4 in Physical habitat simulation for small-sized characid fish species from tropical rivers in Brazil
Fig. 4. The velocities and depth comparison between the field measurement and the numerical model for points in 50% cros- s-section width of the Velhas reach (a-b) and in 50% width of the Curimataí reach (c-d).
FIGURE 4. A in A new small barb (Cyprininae: Smiliogastrini) from the Louesse, Lekoumou (upper Niari basin), and Djoulou (upper Ogowe basin) rivers in the Republic of Congo, west-central Africa
FIGURE 4. A, Known distributional range of Enteromius walshae; yellow stars indicate collection sites and red star indicates collection locality of holotype (AMNH 266856). B, Type locality of holotype, in a small tributary of the Mandoro River (upper Louesse River basin).
FIGURE 1 in A new small barb (Cyprininae: Smiliogastrini) from the Louesse, Lekoumou (upper Niari basin), and Djoulou (upper Ogowe basin) rivers in the Republic of Congo, west-central Africa
FIGURE 1. Enteromius species sampled (table 1), photographed immediately postmortem or in preservation: A, kuiluensis; B, martorelli; C, prionacanthus; D, rouxi, E, rubrostigma; F, trispilomimus; G, walshae new species; H, nigroluteus; I, brichardi; J, camptacanthus; K, chiumbeensis; L, diamounanganai; M, guirali; N, holotaenia; O, jae; P, catenarius; Q, castrasibutum. No tissues are currently available for E. catenarius. Photograph of E. castrasibutum courtesy of Jon Armbruster.
Fig. 2 in Distribution of Siluriformes in a river under the influence of a small hydroelectric power plant of the Paraná River Basin, Brazil
Fig. 2. Mean total abundance of Siluriformes from the Jaguariaiva River, Upper Parana River basin by site [capture-per-unit-effort (CPUE); unit: number of individuals/1,000 m² of nets/16 h]. Vertical bars = standard error.
Fig. 4 in Distribution of Siluriformes in a river under the influence of a small hydroelectric power plant of the Paraná River Basin, Brazil
Fig. 4. Variations in composition of Siluriformes in the three distinct zones in the Nova Jaguaraiva River under the effects of damming. Species richness (beta diversity) was assessed as species dispersion within the three zones using permutational analysis of multivariate dispersions (PERMDISP; e.g., a greater distance to the spatial median indicates a larger dispersion and, therefore, broader beta diversity). The upper and lower hinges correspond to the 25th and 75th quartiles, respectively.
Fig. 1 in Distribution of Siluriformes in a river under the influence of a small hydroelectric power plant of the Paraná River Basin, Brazil
Fig. 1. Location of sampling sites in the Jaguariaiva River, Upper Parana River basin, Brazil: PCH Nova Jaguariaíva (bar); upstream (red circle); reservoir (black circle); downstream (yellow circle).
Fig. 3 in Distribution of Siluriformes in a river under the influence of a small hydroelectric power plant of the Paraná River Basin, Brazil
Fig. 3. Mean abundance of the Siluriformes species from the Jaguariaiva River, Upper Parana River basin by site [capture-per-unit-effort (CPUE); unit: number of individuals/1,000 m² of nets/16 h]. Vertical bars = standard error (Cher, Corydoras ehrhardti; Halb, Hypostomus albopunctatus; Hanc, Hypostomus ancistroides; Hher, Hypostomus hermanni; Hpau, Hypostomus paulinus; Hstr, Hypostomus strigaticeps; Nsel, Neoplecostomus selenae; Rque, Rhamdia quelen; Tcan, Trichomycterus candidus; Cdia, Cambeva diabola).
Dataset in support of an AI-aided chronic mixture risk assessment along a small European river
<p>Here, we make available a dataset to perform an AI-aided multi-scenario chronic mixture risk assessment. In 2021, river-water samples were collected at six sampling sites along the Holtemme River in Central Germany using large-volume solid phase extraction. The extracts were analysed by target chemical analysis for contaminants of emerging concern. The dataset of the chemical analysis was already published and can be found at DOI: 10.5281/zenodo.10892038. Furthermore, a detailed description of the dataset can be found at DOI: 10.1016/j.dib.2024.110510.</p> <p> </p>
A Scene-Level Method for Estimating Small River Widths in Complex Terrain Using Remote Sensing
<p><strong>Files and Descriptions:</strong></p> <p>1. <strong>TP_Lake.csv</strong>: This CSV file contains identified lakes in the Tibetan Plateau.</p> <p>2. <strong>TP_River_Monthly_Statistics.csv</strong>: Monthly statistics for river data on the Tibetan Plateau, including estimations like active channel percentage and width for different river orders.</p> <p>3. <strong>S2RiverWidth.py</strong>: The Python script that contains the main code for river width estimation model. This script includes the functions for preprocessing Sentinel-2 images and predicting river widths.</p> <p>4. <strong>best_model_vCloud10.pth</strong>: The pre-trained deep learning model weights used for river width estimation. This model is a ResNeXt model fine-tuned on our dataset. It accepts Sentinel-2 TOA image with cloud percentage <10% (SCL).</p> <p>5. <strong>Example.tif</strong>: A Sentinel-2 TOA image in .tif format, used for testing the river width estimation model.</p> <p><strong>Model Input Requirements:</strong><br>The model requires a Sentinel-2 TOA image in .tif format as input. The image should be scaled by a factor of 10,000 (with reflectance values range from 0 to 1). The `get_model_input` function automatically crops the image to 224x224 pixels around the center to fit the model's input requirements.</p>
Рис. 2. Низина Λевобережья НТТ в виΑе параΛΛеΛьных берегу моря ваΛов и небоΛьших понижений, вытянутых в северо-восточном направΛении, с характерной раститеΛьностью Fig. 2. The lowland of the left Bank of the LRT in the form of parallel to the seashore shafts and small depressions, elongated in a North-Eastern direction, with characteristic vegetation in Transboundary Migration And The Local Constraints In The Dynamic Of Fish Fauna In The Lower Reaches Of Tumannaya River
Рис. 2. Низина Λевобережья НТТ в виΑе параΛΛеΛьных берегу моря ваΛов и небоΛьших понижений, вытянутых в северо-восточном направΛении, с характерной раститеΛьностью Fig. 2. The lowland of the left Bank of the LRT in the form of parallel to the seashore shafts and small depressions, elongated in a North-Eastern direction, with characteristic vegetation
Рис. 5. РаспреΑеΛение рыб в верхнем бьефе воΑохраниΛища по размерным группам в периоΑ осенней миграции. Размеры рыб: а — меΛкие (Αо 10 см); б — среΑние (10–20 см); в — крупные (боΛее 20 см) Fig. 5. Distribution of fish upstream of the reservoir by size during the autumn migration. Fish sizes: а — small (under 10 cm); b — medium (10–20 cm); c — large (exceeding 20 cm) in Dynamics and current status of the Amazar River ichthyofauna after the construction of the PPM «Polyarnaya» hydroelectric complex
Рис. 5. РаспреΑеΛение рыб в верхнем бьефе воΑохраниΛища по размерным группам в периоΑ осенней миграции. Размеры рыб: а — меΛкие (Αо 10 см); б — среΑние (10–20 см); в — крупные (боΛее 20 см) Fig. 5. Distribution of fish upstream of the reservoir by size during the autumn migration. Fish sizes: а — small (under 10 cm); b — medium (10–20 cm); c — large (exceeding 20 cm)
Fig. 2 in Short communication First record of eyeless specimens of Gammarus roeselii Gervais 1835 (Amphioda, Gammaridae) in a small stream of the sub-lacustrine Ticino River basin (Lombardy, Northern Italy)
Fig. 2 - Eyeless specimens collected in the Venara Stream, one of the small right bank tributaries of the Ticino River.
Figure 2 in Communities of the Bidentetea class of small coastal river valleys of the Western Pomerania (Poland)
Figure 2. The numerical classification of relevés from rivers of the Wałcz Plain – dendrogram (1-68 – numbers of relevés; A – comm. with Polygonum minus; B – Chenopodietum rubri Timar 1947; C – Bidentetum cernui Kobendza 1948; Da-Df – Bidenti-Polygonetum hydropiperis (Miljan 1933) Lohmeyer in R.Tx. 1950 nom invers).
Text-fig. 3 Pollen diagram from the locality of Bohutín. 0-0.01 m – sandy soil mixed with humus, slightly clayey, sample B11; 0.05 m – grey-blue strongly sandy clay, sample B10; 0.10-0.25 m – brown-grey sandy clay with plant remains and mixed with a small amount of peat, sample B9, sample B8 (0.15 m), sample B7 (0.20 m), sample B6 (0.25 m); 0.30-0.35 m – dark sandy clay mixed with peat and plant remains, sample B5, sample B4 (0.35 m); 0.40 m – grey strongly sandy clay mixed with peat, sample B3; 0.45-0.50 m – grey-blue strongly sandy clay, sample B2, sample B1 (0.50 m). in Reconstruction Of Vegetation Development On The Floodplain Of The Litavka River In The Holocene (Central Bohemia, Brdy Mts.)
Text-fig. 3 Pollen diagram from the locality of Bohutín. 0-0.01 m – sandy soil mixed with humus, slightly clayey, sample B11; 0.05 m – grey-blue strongly sandy clay, sample B10; 0.10-0.25 m – brown-grey sandy clay with plant remains and mixed with a small amount of peat, sample B9, sample B8 (0.15 m), sample B7 (0.20 m), sample B6 (0.25 m); 0.30-0.35 m – dark sandy clay mixed with peat and plant remains, sample B5, sample B4 (0.35 m); 0.40 m – grey strongly sandy clay mixed with peat, sample B3; 0.45-0.50 m – grey-blue strongly sandy clay, sample B2, sample B1 (0.50 m).
Linked collectors and determiners for: Occurrence records of small and medium sized mammal species in Tana River Basin, Kenya.
Natural history specimen data linked to collectors and determiners held within, "Occurrence records of small and medium sized mammal species in Tana River Basin, Kenya". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d">https://bionomia.net/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d">https://gbif.org/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d</a>. Formatted as a Frictionless Data package.
FIGURE 6. A in A new small barb (Cyprininae: Smiliogastrini) from the N'sele and Mayi Ndombe rivers in the lower reaches of the middle Congo basin (Democratic Republic of Congo, Central Africa)
FIGURE 6. A, Distributional range of "Barbus" validus: yellow stars indicate collection sites and blue star indicates collection locality of holotype; B, typical habitat of "Barbus" validus in the Mayi Ndombe River.
FIGURE 4 in A new small barb (Cyprininae: Smiliogastrini) from the N'sele and Mayi Ndombe rivers in the lower reaches of the middle Congo basin (Democratic Republic of Congo, Central Africa)
FIGURE 4. Neurocrania in dorsal view: A, "Barbus" validus, AMNH 258938; B, "Barbus" humeralis, AMNH 247409; C, "Barbus" miolepis, AMNH 250765. Arrows indicate location of occipital foramina.
FIGURE 3 in A new small barb (Cyprininae: Smiliogastrini) from the N'sele and Mayi Ndombe rivers in the lower reaches of the middle Congo basin (Democratic Republic of Congo, Central Africa)
FIGURE 3. "Barbus" validus, new species: A, head in lateral view; B, isolated infraorbital series; C, head in dorsal view. White outlines indicate the location of tubercles.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.